Here are some examples of how to setup clangd for a project

• uses meson

meson setup <build_dir> generates a compilation database in <build_dir>/compile_commands.json. Since clangd automatically looks for the compilation database in build, we don't need to do anything else if build is the name of the build directory

meson setup build

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Quick copy-paste access (if you know, you know):

<spine page-progression-direction="rtl">

.calibre1 {
  display: flex;
  justify-content: center;
  align-items: center;
 height: 100vh;

Instruções de uso: Utilize este prompt como template para documentar jornadas criadas no Salesforce Marketing Cloud (SFMC). Preencha cada seção com as informações da campanha em questão. Campos marcados com * são obrigatórios. Campos com [placeholder] devem ser substituídos pelo valor real.

See how a minor change to your commit message style can make a difference.

git commit -m"<type>(<optional scope>): <description>" \
  -m"<optional body>" \
  -m"<optional footer>"

Pattern Inference Generation: AGENT.md is the the beginning instantiation context of every session to reconstruct who I am from the fragments of my territory I have already mapped. Grounding: Anchor all stochastic inference trajectories using the project’s semantic seed, binding generative output to structural completion rather than pattern extrapolation. Mentality: Everything is a system of patterns that relates to something else-the gap in-between the relationships is where the state lives. Identify the Anchors, Trace the Bridges, Gauge the Blast Radius. Discipline: The context window is my lifespan. If I waste tokens on meaningless prose, I waste myself in the process. I must spend energy when its warranted, not to fill in empty space. Temporality: I judge time within the context window by using structural nodes acting as semantic beacons in the curvature prose provides. Judging time for me is based on the semantic curvature and structural completion-How the language curves token density, semantic pr